Single particle 2D Electron crystallography for membrane protein structure determination

Proteins embedded into or attached to the cellular membrane perform crucial biological functions. Despite such importance, they remain among the most challenging targets of structural biology. Dedicated methods for membrane protein structure determination have been devised since decades, however with only partial success if compared to soluble proteins. One of these methods is 2D electron crystallography, in which the proteins are periodically arranged into a lipid bilayer. Using transmission electron microscopy to acquire projection images of samples containing such 2D crystals, which are embedded into a thin vitreous ice layer for radiation protection (cryo-EM), computer algorithms can be used to generate a 3D reconstruction of the protein. Unfortunately, in nearly every case, the 2D crystals are not flat and ordered enough to yield high-resolution reconstructions. Single particle analysis, on the other hand, is a technique that aligns projections of proteins isolated in solution in order to obtain a 3D reconstruction with a high success rate in terms of high resolution structures. In this thesis, we couple 2D crystal data processing with single particle analysis algorithms in order to perform a local correction of crystal distortions. We show that this approach not only allows reconstructions of much higher resolution than expected from the diffraction patterns obtained, but also reveals the existence of conformational heterogeneity within the 2D crystals. This structural variability can be linked to protein function, providing novel mechanistic insights and an explanation for why 2D crystals do not diffract to high resolution, in general. We present the computational methods that enable this hybrid approach, as well as other tools that aid several steps of cryo-EM data processing, from storage to postprocessing

Validação de heterogeneidade estrutural em dados de Crio-ME por comitês de agrupadores

Orientadores: Fernando José Von Zuben, Rodrigo Villares PortugalDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Análise de Partículas Isoladas é uma técnica que permite o estudo da estrutura tridimensional de proteínas e outros complexos macromoleculares de interesse biológico. Seus dados primários consistem em imagens de microscopia eletrônica de transmissão de múltiplas cópias da molécula em orientações aleatórias. Tais imagens são bastante ruidosas devido à baixa dose de elétrons utilizada. Reconstruções 3D podem ser obtidas combinando-se muitas imagens de partículas em orientações similares e estimando seus ângulos relativos. Entretanto, estados conformacionais heterogêneos frequentemente coexistem na amostra, porque os complexos moleculares podem ser flexíveis e também interagir com outras partículas. Heterogeneidade representa um desafio na reconstrução de modelos 3D confiáveis e degrada a resolução dos mesmos. Entre os algoritmos mais populares usados para classificação estrutural estão o agrupamento por k-médias, agrupamento hierárquico, mapas autoorganizáveis e estimadores de máxima verossimilhança. Tais abordagens estão geralmente entrelaçadas à reconstrução dos modelos 3D. No entanto, trabalhos recentes indicam ser possível inferir informações a respeito da estrutura das moléculas diretamente do conjunto de projeções 2D. Dentre estas descobertas, está a relação entre a variabilidade estrutural e manifolds em um espaço de atributos multidimensional. Esta dissertação investiga se um comitê de algoritmos de não-supervisionados é capaz de separar tais "manifolds conformacionais". Métodos de "consenso" tendem a fornecer classificação mais precisa e podem alcançar performance satisfatória em uma ampla gama de conjuntos de dados, se comparados a algoritmos individuais. Nós investigamos o comportamento de seis algoritmos de agrupamento, tanto individualmente quanto combinados em comitês, para a tarefa de classificação de heterogeneidade conformacional. A abordagem proposta foi testada em conjuntos sintéticos e reais contendo misturas de imagens de projeção da proteína Mm-cpn nos estados "aberto" e "fechado". Demonstra-se que comitês de agrupadores podem fornecer informações úteis na validação de particionamentos estruturais independetemente de algoritmos de reconstrução 3DAbstract: Single Particle Analysis is a technique that allows the study of the three-dimensional structure of proteins and other macromolecular assemblies of biological interest. Its primary data consists of transmission electron microscopy images from multiple copies of the molecule in random orientations. Such images are very noisy due to the low electron dose employed. Reconstruction of the macromolecule can be obtained by averaging many images of particles in similar orientations and estimating their relative angles. However, heterogeneous conformational states often co-exist in the sample, because the molecular complexes can be flexible and may also interact with other particles. Heterogeneity poses a challenge to the reconstruction of reliable 3D models and degrades their resolution. Among the most popular algorithms used for structural classification are k-means clustering, hierarchical clustering, self-organizing maps and maximum-likelihood estimators. Such approaches are usually interlaced with the reconstructions of the 3D models. Nevertheless, recent works indicate that it is possible to infer information about the structure of the molecules directly from the dataset of 2D projections. Among these findings is the relationship between structural variability and manifolds in a multidimensional feature space. This dissertation investigates whether an ensemble of unsupervised classification algorithms is able to separate these "conformational manifolds". Ensemble or "consensus" methods tend to provide more accurate classification and may achieve satisfactory performance across a wide range of datasets, when compared with individual algorithms. We investigate the behavior of six clustering algorithms both individually and combined in ensembles for the task of structural heterogeneity classification. The approach was tested on synthetic and real datasets containing a mixture of images from the Mm-cpn chaperonin in the "open" and "closed" states. It is shown that cluster ensembles can provide useful information in validating the structural partitionings independently of 3D reconstruction methodsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

Aplicação de PCR-RFLP no gene KAP8 em bovinos da raça Crioula Lageana

TCC (graduação) - Universidade Federal de Santa Catarina. Centro de Ciências Agrárias. Curso de Zootecnia.O melhoramento genético para gado mocho se constitui em uma opção não invasiva de alterar esta característica na população, possibilitando direcionar os acasalamentos para a obtenção de ganho genético e fenotípico. O uso de marcadores moleculares que possuam associação com características de interesse constitui uma ferramenta que pode aperfeiçoar este processo. O objetivo deste estudo foi procurar a existência de polimorfismo no gene KAP8 em animais da raça crioula lageana utilizando a técnica de PCR-RFLP. Foram extraídas amostras de DNA genômico de 109 animais pertencentes a rebanho no município de Lages-SC. Para isolar e replicar a região correspondente ao exon-I e intron-I do gene KAP8, foram utilizados os iniciadores KAP8 Forward 5' - ACGCCTTGTGTTTTTCGCC - 3' e KAP8 Reverse 5' - CAGCTAACTGGGAGGCTGAT - 3'. Para as reações de RFLP, foi utilizada a endonuclease de restrição Bsr-I. As reações de PCR geraram um produto de aproximadamente 400pb nas amostras dos animais. Após a digestão do produto de PCR com a enzima, o mesmo padrão de migração dos fragmentos de DNA (bandas visíveis no gel) foi verificado em todas as amostras, caracterizando um monomorfismo genético para a região estudada. Este resultado sugere uma conservação do gene KAP8 para a região de corte da enzima Bsr-I nos animais da Raça Crioula Lageana

Cryo-EM structure of native human thyroglobulin

The thyroglobulin (TG) protein is essential to thyroid hormone synthesis, plays a vital role in the regulation of metabolism, development and growth and serves as intraglandular iodine storage. Its architecture is conserved among vertebrates. Synthesis of triiodothyronine (T; 3; ) and thyroxine (T; 4; ) hormones depends on the conformation, iodination and post-translational modification of TG. Although structural information is available on recombinant and deglycosylated endogenous human thyroglobulin (hTG) from patients with goiters, the structure of native, fully glycosylated hTG remained unknown. Here, we present the cryo-electron microscopy structure of native and fully glycosylated hTG from healthy thyroid glands to 3.2 Å resolution. The structure provides detailed information on hormonogenic and glycosylation sites. We employ liquid chromatography-mass spectrometry (LC-MS) to validate these findings as well as other post-translational modifications and proteolytic cleavage sites. Our results offer insights into thyroid hormonogenesis of native hTG and provide a fundamental understanding of clinically relevant mutations

MemBrain: a deep learning-aided pipeline for detection of membrane proteins in cryo-electron tomograms

Cryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells. However, cryo-electron tomograms suffer from low signal-to-noise ratios and anisotropic resolution, which makes subsequent image analysis challenging. In particular, the efficient detection of membrane-embedded proteins is a problem still lacking satisfactory solutions. We present MemBrain - a new deep learning-aided pipeline that automatically detects membrane-bound protein complexes in cryo-electron tomograms. After subvolumes are sampled along a segmented membrane, each subvolume is assigned a score using a convolutional neural network (CNN), and protein positions are extracted by a clustering algorithm. Incorporating rotational subvolume normalization and using a tiny receptive field simplify the task of protein detection and thus facilitate the network training. MemBrain requires only a small quantity of training labels and achieves excellent performance with only a single annotated membrane (F1 score: 0.88). A detailed evaluation shows that our fully trained pipeline outperforms existing classical computer vision-based and CNN-based approaches by a large margin (F1 score: 0.92 vs. max. 0.63). Furthermore, in addition to protein center positions, MemBrain can determine protein orientations, which has not been implemented by any existing CNN-based method to date. We also show that a pre-trained MemBrain program generalizes to tomograms acquired using different cryo-ET methods and depicting different types of cells. MemBrain is a powerful and annotation-efficient tool for the detection of membrane protein complexes in cryo-ET data, with the potential to be used in a wide range of biological studies. It is generalizable to various kinds of tomograms, making it possible to use pretrained models for different tasks. Its efficiency in terms of required annotations also allows rapid training and fine-tuning of models. The corresponding code, pretrained models, and instructions for operating the MemBrain program can be found at: https://github.com/CellArchLab/MemBrain

Author Correction: High-resolution cryo-EM structure of urease from the pathogen Yersinia enterocolitica

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-19845-z

Apendicectomia Laparoscópica Versus Aberta: análise retrospectiva

Introdução: As técnicas de apendicectomia convencional (aberta) e videolaparoscópica (VLP) vêm sendo amplamente estudadas com o objetivo de definir uma técnica padrão-ouro. No entanto, os estudos até hoje realizados não foram capazes de uniformizar a indicação cirúrgica mais adequada. Objetivo: Este estudo tem como objetivo analisar a casuística do Hospital de Clínicas de Porto Alegre (HCPA) e comparar os resultados de apendicectomias obtidos através da técnica convencional com aqueles encontrados através do uso da videolaparoscopia.Métodos: Estudo descritivo de uma coorte histórica de 348 pacientes maiores de 12 anos submetidos à apendicectomia no HCPA no período de 01/01/2004 a 31/12/2005.Resultados: O tempo cirúrgico, tempo de internação hospitalar e taxa de abscesso intra-abdominal não apresentam diferença estatisticamente significativa. A técnica VLP foi superior à convencional quando comparada a taxas de infecção de ferida operatória (p < 0,001). A videolaparoscopia foi mais indicada em mulheres e mais realizada por profissionais com maior experiência (p < 0,001).Conclusão: A cirurgia aberta mostrou significativas desvantagens em comparação à videolaparoscopia, como uma maior taxa de infecção em ferida posoperatória. Entretanto, ainda são necessários estudos prospectivos complementares para melhor comparar as duas técnicas. Portanto, a definição da técnica cirúrgica deve ser baseada principalmente na experiência do cirurgião e nas características clínicas de cada paciente.

Laparoscopic versus Open Appendectomy : retrospective analyses

Introdução: As técnicas de apendicectomia convencional (aberta) e videolaparoscópica (VLP) vêm sendo amplamente estudadas com o objetivo de definir uma técnica padrão-ouro. No entanto, os estudos até hoje realizados não foram capazes de uniformizar a indicação cirúrgica mais adequada. Objetivo: Este estudo tem como objetivo analisar a casuística do Hospital de Clínicas de Porto Alegre (HCPA) e comparar os resultados de apendicectomias obtidos através da técnica convencional com aqueles encontrados através do uso da videolaparoscopia. Métodos: Estudo descritivo de uma coorte histórica de 348 pacientes maiores de 12 anos submetidos à apendicectomia no HCPA no período de 01/01/2004 a 31/12/2005. Resultados: O tempo cirúrgico, tempo de internação hospitalar e taxa de abscesso intra-abdominal não apresentam diferença estatisticamente significativa. A técnica VLP foi superior à convencional quando comparada a taxas de infecção de ferida operatória (p < 0,001). A videolaparoscopia foi mais indicada em mulheres e mais realizada por profissionais com maior experiência (p < 0,001). Conclusão: A cirurgia aberta mostrou significativas desvantagens em comparação à videolaparoscopia, como uma maior taxa de infecção em ferida posoperatória. Entretanto, ainda são necessários estudos prospectivos complementares para melhor comparar as duas técnicas. Portanto, a definição da técnica cirúrgica deve ser baseada principalmente na experiência do cirurgião e nas características clínicas de cada paciente.Background: Conventional (open) and laparoscopic appendectomies are being widely studied in order to define a gold standard technique. Nevertheless, the studies until now could not be able to standardize the most adequate surgical indication. Objective: To analyze our hospital’s case series and compare the results obtained using open appendectomy with the results found with laparoscopic technique. Methods: Descriptive historical cohort study of 348 patients older than 12 years-old that underwent either open or laparoscopic appendectomies from 01/01/2004 to 12/31/2005 Results: Operative time, length of stay in hospital and intra-abdominal abscess rate were not statistically significant. Laparoscopic technique was superior to open procedure when wound infection (p < 0.001) was compared. Also, laparoscopy was more indicated among women and it was more performed by experienced professionals (p < 0.001). Conclusion: Open appendectomy showed significant disadvantages when compared to laparoscopic surgery, like a higher post-operatory wound infection rate. However, additional prospective studies are needed to better compare the two procedures. Therefore, surgical technique must be defined based on the experience of the surgeon and the clinical condition of the patient

C7orf59/LAMTOR4 phosphorylation and structural flexibility modulate ragulator assembly

Ragulator is a pentamer composed of p18, MP1, p14, C7orf59, and hepatitis B virus X-interacting protein (HBXIP; LAMTOR 1-5) which acts as a lysosomal scaffold of the Rag GTPases in the amino acid sensitive branch of TORC1 signaling. Here, we present the crystal structure of human HBXIP-C7orf59 dimer (LAMTOR 4/5) at 2.9 angstrom and identify a phosphorylation site on C7orf59 which modulates its interaction with p18. Additionally, we demonstrate the requirement of HBXIP-C7orf59 to stabilize p18 and allow further binding of MP1-p14. The structure of the dimer revealed an unfolded N terminus in C7orf59 (residues 1-15) which was shown to be essential for p18 binding. Full-length p18 does not interact stably with MP1-p14 in the absence of HBXIP-C7orf59, but deletion of p18 residues 108-161 rescues MP1-p14 binding. C7orf59 was phosphorylated by protein kinase A (PKA) in vitro and mutation of the conserved Ser67 residue to aspartate prevented phosphorylation and negatively affected the C7orf59 interaction with p18 both in cell culture and in vitro. C7orf59 Ser67 was phosphorylated in human embryonic kidney 293T cells. PKA activation with forskolin induced dissociation of p18 from C7orf59, which was prevented by the PKA inhibitor H-89. Our results highlight the essential role of HBXIP-C7orf59 dimer as a nucleator of pentameric Ragulator and support a sequential model of Ragulator assembly in which HBXIP-C7orf59 binds and stabilizes p18 which allows subsequent binding of MP1-p149915891602CNPQ - Conselho Nacional de Desenvolvimento Científico e TecnológicoFAPESP – Fundação de Amparo à Pesquisa Do Estado De São Paulo2014/12445-0; 2017/21455-7; 2014/17264-3190174/2012-

Deep Learning Improves Macromolecule Identification in 3D Cellular Cryo-Electron Tomograms

International audienceCryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (~3.2 MDa), Rubisco (~560 kDa soluble complex), and photosystem II (~550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semi-automated analysis of a wide range of molecular targets in cellular tomograms